A balanced ration is important to achieve a high production and keep healthy cows. And there comes much more to feeding management then just loading and unloading the feed. It’s a challenge every day to make sure you put together the most optimal ration, exactly as it was invented on paper. Since feed is becoming more and more expensive, and milk prices are not getting significantly higher. It is becoming increasingly important to have insight the amount of feed that is fed and the costs of this feed. A weighing sensor makes it easier to feed accurately. First, all ingredients have to be imported in the program and possibly the costs per kg of product or dry matter. After selecting the ration, the system indicates how much you have to load. It measures the weight of the ration and sends the results to the modem screen in the tractor. The farmer can now see exactly how much feed is in the mixer and how much he still has to load therefore the calculated ration can be loaded exactly. The benefits are that the farmer can be sure that the ration is consistent regardless of the person who is feeding. Measuring is knowing! If you monitor the feeding more efficiently and you know how much rest feed there is, you can say exactly how much feed was needed to produce these amounts of milk. This enables the farmers to manage on feed efficiency by changing the ration and monitoring what this does to the milk production. Accurate feeding can save a lot of money.

Hanno Jaakson and Priit Karis, Estonian University of Life Sciences
Understanding cows’ body condition score (BCS) is a valuable tool in the early identification of health and feeding problems and also extended periods and extent of negative energy balance (NEB) post partum. This is becoming more of a problem as cow milk yields increase and the ability to match intakes to requirements becomes more difficult to manage. Identifying NEB early in cows at risk is of great benefit to farmers. Manually assessing BCS is time consuming and to do so accurately takes skill and experience, while automatic devices can save time and labour and, if accurate, can give early warning of problems to farmers. A DeLaval automatic BCS device was tested on a 600-cow Holstein-Friesian dairy farm in Estonia. Sixty-six cows were compared using the automatic system and with trained assessors using visual assessment with a classic five-point BCS scale. The two methods gave very close scores, the manual assessment very slightly underscoring compared with the automatic system. This preliminary evaluation shows that the system works well and can be used by farmers to quickly and reliably identify those cows with too low BCS and allow the early management of that cow to prevent the problem from worsening.

One of most important factors that affects dairy cow productivity as well as overall body condition is the climate conditions in cowshed, especially the air humidity and temperature levels. In Eastern Europe located farms characterizes with extremely high changes of air temperatures in-between seasons – hot and humid summers (+25 – 300C) and cold and humid winters (-20 - -250C) and in recent cases there are severe changes of environmental temperature during short periods of time. Therefore, in dairy farms, climate control systems are crucial.
In most of modern farms automatic climate control systems are included up until some extent – either it is automatically controlled air ventilators or automatic curtain system or automatic heaters in strategic points of cowshed.
The system reads and analyzes the temperature and average humidity level throughout the cowshed and sends signal to open or close curtains and turn on/off ventilators and heaters. The system equipped in dairy farm (600 dairy cows) also contained automatic daylight saving – it turns lights on or off depending on the outside lighting. This system allows to save additional money for farmer from the lowered electro energy expenses that comes from useless lighting of cowshed.
Nevertheless, some of climate control systems in dairy farms are equipped with water misters next to feeding tables and in waiting area before milking parlor. That allows reduce the negative effects of heat in hot summers.
The automatic climate control in farm showed positive impact on cow welfare and overall wellbeing of cows. With the introduction of cowshed climate control system in farm, the number of cold stress decreased by 75%, but number of heat stress cases decreased by 50%.

In modern dairy farming conditions, the need for precise, balanced and continuous feed distribution method becomes crucial. One of methods to ensure the satisfaction of all mentioned needs is automatic feed ration mixers and distributers.
In family owned farm with 160 dairy cows, after long and unsuccessful search for local labor and cost analysis of traditional feed distribution, in year 2010 was introduced automatic feeding system. System in farm is equipped with feed storage stations, ration mixer and distributer, measuring lasers for feed quantity assessments and feed pusher.
The system is programmed to feed each cow group once in four hours that ensures that even in nights on the feeding table will be available fresh feed. In system it is possible to prepare and distribute feed ration individually for each cow group.
One of main advantages of the system in farm was lowered need for manual labor as well as more precise and continuous distribution of feed. The automatic feeding system also shows significant impact on cow welfare, especially with the lowering of stress factors.
With the introduction of automatic feeding station in the farm cow average milk productivity increased by 3750 kg with additional increase of milk fat and protein content. In addition to that in farm decreased the number of cows with different traumas, because of lowered hustling at feeding table.
No less important is the fact that farm owner does not need any additional labor for cow feeding organization. The systems feed storage can store silage for up to 5 days that allows famer to be more flexible with his time management, therefore improving his quality of life.

The automatic milking systems or milking robots are one of most introduced technologies in Baltic state dairy farms in last 5 years. They are usually introduced because of lack of capable workforce and because of their positive impact on dairy cow welfare (lowered stress factor impact). The automatic milking system ensures high quality udder disinfection before and after milking as well as standardized milking procedure without any human interaction.
Introduction of milking robots usually related to high levels of stress for animals at the beginning of introduction of the system, but later the stress levels for the cows milked by robot is significantly lower than it is in cow groups in that are milked in milking parlors. The lower stress is usually linked with standardized milking procedure that is repeated in every milking and does not scare animals.
The common practice in dairy farms where are introduced milking robots shows that by doing that the milk productivity increases significantly – after adaptation period the amount of milk obtained in one day increases by 15 – 35%, depending on the in-farm conditions before installation of automatic milking systems.
Introduction of milking robots in dairy farms usually comes with increased quality of obtained milk, because the system fully excludes the possibility for milk to interact with air and the udder disinfection is done more carefully. In farms with milking robots, introduced in last 5 years (from year 2013) the amount of somatic cells in milk had lowered by 50 – 75%.

The effectiveness of ration quality, the state of cows metabolic and overall health shows significant impact on their body condition. In the large groups of animals, it is almost impossible to notice the changes of the body condition (BC) of one cow, but, by introducing modern technologies into cows life, it is possible to have cow BC score measurements several times per day. One of such technologies is cow body condition scoring camera, usually located before milking parlor. This camera is reading data every time when cow enters milking parlor gates (2 – 3 measurements per day). This system allows to follow the BC of each individual animal and spot any deviations from norm. The knowledge about BC score of individual animal and cow group serves as helpful indicator on quality of prepared feed ration. By using the data about cow BC and analyzing the correlation with milk composition data it is possible to evaluate the feeding efficiency as well as the metabolic state of each individual cow and in cow group.
In the farm with 100 dairy cows BC scoring camera were introduced in year 2011. In this time the number of cows with metabolic disorders decreased by 68%, milk productivity increased by 2800 kg (25% increase) and calving interval decreased by 46 days. In the farm BC scoring cameras are used for determination of the feed ration effectiveness and its impact on cows. The feed ration is adapted if there are negative response on the quality or ratio of different feedstuff.

Katri Ling and David Arney
Estonian University of Life Sciences
Alongside recent increases in dairy cow milk yields is a concomitant decrease in the cows’ fertility. The causes of these reductions in fertility may be multiple, but the outcome for the farmer is increased calving intervals and premature culling leading to impaired efficiency and consequent economic losses. Recording milk progesterone can potentially accurately identify the timing of oestrus and pinpoint the optimum time for successful insemination, allowing the farmer to avoid missing heats and reducing the calving interval. A large dairy farm in Estonia, with approximately 400 cows and a high average milk yield of 11,000 kg per year, has been involved in a pilot project with Estonian Livestock Performance Recording Ltd to test progesterone routinely in their cows using the DeLaval Herd Navigator™ system. The farm management are very satisfied with the results from their use of this system, with the calving interval having been reduced from 410 days when the project started to 389 days. In part as a consequence of these findings, four farms have now started to use this system in Estonia.

The proportion of automatic milking systems (AMS) is continuously increasing throughout Europe. Robotic milking offers great advantages in terms of labour flexibility and data collection, but comes with a steep learning curve. One of the biggest challenges for farmers using AMS, is the high number of false mastitis alerts. So how can dairy farmers distinguish true from false alerts?
Every commercial AMS model uses a different method to generate a mastitis alarm. The most frequently used factors for monitoring mastitis, however, are the electrical conductivity of milk and milk yield measurements. Both can be measured per quarter. Theoretically, visually inspecting every single mastitis alarm in the barn is the best option to detect clinical mastitis – but this would result in an impossible workload.
The first step in controlling mastitis on AMS farms, is checking the computer at least twice a day. The software will automatically generate “attention lists”, highlighting the cows that require the farmer’s attention. Still, not every cow on the attention list has mastitis, and not every cow with mastitis requires an antibiotic treatment. Combining multiple variables (electrical conductivity, milk yield, color alerts, …) with the cow’s known history (days in lactation, milking interval, …) is essential for properly evaluating mastitis alerts. Cows that turn up more than once on the attention list should definitely be kept an eye on.

Roughage is the main feed for dairy cows. When the feed is ensiled, it will be analysed to determine the quality. The quality of the roughage is depending on factors like cutting date, the quality of the grass or corn silage and weather conditions at time of ensiling. Between ensiling and actual usage of the silage, changes can occur. It’s important to know what the quality of the roughage is at the moment of feeding. When the farmer knows the quality of the roughage, he can estimate the amount of extra concentrate for an optimal animal performance.
The SCIO scanner, at the moment only available for the Animal Feed industry but can be used on dairy farms, is a relatively new technology which can determine the nutritional value of feed by scanning and using the light spectrum. The farmer can use SCIO to troubleshoot animal feed variations and adjust rations, track dry matter regularly, monitor trends to avoid unexpected milk yield drop due to feed inconsistencies.
This SCIO allows for real time testing and is more accurate and simpler to use than the cumbersome on-farm alternatives. The times needed for making 3-10 scans is short: it only takes about two minutes. This tool can be used for silage but also on any other type of animal feed. It help to compose the most optimal ration for dairy cows.

Blanket dry cow therapy, meaning all cows receive an infusion of antimicrobials in their 4 quarters at dry off, has been standard practice for years. However, with growing concerns for antimicrobial resistance, more farms are shifting towards selective dry cow therapy. This means you are only going to treat the animals that are suspected of having an infection. But how do you select the cows that should get antimicrobials? Use data!
Cows with:
- No clinical mastitis in the previous lactation
- Milk production lower than 15 kg
- Somatic cell count at the 3 latest controls lower than 150.000 (heifers) and 100.000 cell/ml (cow)
… can be selected for dry off without antibiotics. In all other situations, you can take a milk sample for culturing. Good dry off management without antibiotics is possible, but excellent record keeping and hygiene at dry-off is crucial. Possible benefits of drying off without antibiotics include reducing the risk of antibiotic resistance while saving money in the process.

Condition score is determined by many dairy farmers by looking at and feeling the cow. This has to be done regularly, to get a good insight in the development of the condition score. This is a time-consuming job. New technology offers a solution for dairy farmers who want to measure the condition score of the cows in a more efficient way. The BCS camera of DeLaval says farewell to the human scoring and the inaccuracy of looking and feeling. This system automatically scores the body condition score of every cow in the herd. The BCS camera is integrated into the milking system or placed at the selection gate and makes 3D images of the back of the cow when she passes the camera. This images are analysed and a score is given to the animal. Farmers can see this score on the computer in the BCS software. As soon as a cow deviates from the farm specific condition progress of the herd, the farmer receive an attention and can optimize the management of the herd. The advantage of the BCS camera is that, depending on the placement of the BCS camera, it is measured daily and accurately without the cows noticing it. In addition, the automatic way of scoring the conditions ensures considerable time saving compared to manual scoring. The farmer also has a great insight into the herd and can further optimize the farm to produce as efficiently as possible. An additional advantage is that the BSC camera can be connected to the concentrate feed box for a optimal ration.

The new sensors that can be used for monitoring behavior of cows will add on knowledge that favors productivity, health and welfare of the cows. There is a general target that cows have to rest at least 10 hours a day. Less resting has been connected with claw disease and lameness. Excessive standing will motivate cows to lie down before eating. This impairs both animal welfare and production. However, there are a lot of variation depending on differences in housing systems. Rubber mats in the alleys will decrease resting times a little as they are more comfortable to stand on. Also grazing affects standing-time, at group level. Individual increase in standing time can be seen in herds that are overcrowded and in herds with poor introduction of heifers. Cows at risk for health disorders can be identified when resting, during periods when the rest of the herd is eating. In robotic-milking-herds it can be difficult to identify these cows, but comparing resting patterns of individual cows vs. herd-level can be of great help. It can be of interest to study how much cows are standing around milking. Excessive standing, 2-3 hours prior to milking can be an indicator of poor milking management in conventional milking systems or poor management/cow traffic systems in robotic milking systems. Even though, there are technologies available to monitor activity the data are not fully explored. More advanced analysis is needed, e.g. to combine information on presence at the feeding rack, assuming cows are eating, with activity in general, like standing and resting. This information can help farmers to e.g. improve feeding frequency and to enhance feed intake to get better productivity and also ensure that all cows in the herd get their proper resting times.

The fresh period of a cow is a critical and challenging time. The immune system is many times surpressed, the cow is recovering from calving, the milk production takes off, her environment changes when she is moved from the dry pen to a milking group, and the amount and type of feed given is changed. At the same time we expect the cow to perform her very best and come up to the maximum milk production of her genetic potential. In order to do that she must stay healthy, comfortable and able to consume the amount of feed needed for that milk production level. Monitoring the fresh cows for metabolic disturbances for early intervention is crucial. As the energy demand from the milk production exceeds the amount she is able to consume from the feed, she starts to take from the fat reserves in her body and negative energy balance occurs. Keep a close look on the body condition level to make sure that she is not dropping too fast and too much. Supplying fresh tasty feed with sufficient nutrient content is a must. It is a constant balancing act to stay on the healthy and productive side of being an efficient dairy cow instead of turning into negative numbers in the books. All the hard work put into this critical period will reward you later on.

Feed management is one of the major concerns on any dairy goat farm. On a technical level, rationing has a huge impact on milk production. It accounts for 40-70% of the milk yield. In a questionnaire completed by 35 dairy goat farmers, only 9.7% of the farmers indicate to calculate the rations themselves, while 67.7% indicates the willing to do it themselves.
This observation was one of the reasons to establish Farmdesk (www.farmdesk.eu), a spin-off of Wim Govaerts & Co, one of the 4D4F project partners. Farmdesk is an on-line software tool that consists of a Milk, Feed and Economy module. The Feed module allows farmers to administer their feeds, and to calculate rations in a very graphical, user-friendly way.
By presenting the ration in a graphical way, farmers pick up insights much quicker. They learn to know the various fodders. Also, Farmdesk incorporates animal signals (body condition score, manure consistency, milk data) into account to give hands-on advice to adjust rations accordingly. Next to this, a farmer can connect his/her farm to his/her preferred advisor. In this way, the communication process between farmer and advisor is much more efficient. The farmer pays less on consultancy hours, the advisor gains a lot of time not searching/mailing/calling for data, he sees and communicates it on-line.

Goat milk production results contain an enormous amount of useful data. Based upon production numbers, fat and protein levels, urea levels, cel counts and plate counts (both on global farm level as on individual animal level), farmers should continuously make decisions. However, many dairy goat farmers admit not to have enough insights on the data.
This observation was the reason to establish Farmdesk (www.farmdesk.eu), a spin-off of Wim Govaerts & Co, one of the 4D4F project partners. Farmdesk is an on-line software tool that consists of a Milk, Feed and Economy module. The Milk module collects all milk data through automatic data connections. Farmdesk visualizes the data and gives automatic attentions by smart algorithms.
Farmdesk and its mobile app give automatic push notifications to farmers in case of attentions. In this way, farmers keep track on this, also in busy periods e.g. in field seasons. On a technical-economical level, preventing heat stress issues (observable by low fat/protein ratios) by adding rumen buffers, preventing ketosis (observable by high fat/protein ratios) by adding more energy or maximizing milk production by monitoring the urea levels, are ways to prevent economical losses that can quickly rise till 10000 EUR on an average dairy goat farm.

Feed is the major cost on any dairy goat farm. It accounts for 30-50% of the total cost price. It is clear that farmers should manage this very thoroughly. Nevertheless, in a questionnaire completed by 35 dairy goat farmers, 53.3% of the farmers indicate not to have (enough) insights on economical KPI’s like feed cost, feed efficiency, feed profit, total cost price…
This observation was one of the reasons to establish Farmdesk (www.farmdesk.eu), a spin-off of Wim Govaerts & Co, one of the 4D4F project partners. Farmdesk is an on-line software tool that consists of a Milk, Feed and Economy module. The Economy module allows farmers to calculate the major economical KPI’s on a regular basis, to keep track on it. By collection data from the Milk and Feed module, the calculation is very quick with only a handful of manual inputs.
Many farmers rely for a huge part on ration advice by commercial feed suppliers. Farmers should pay attention that they keep track on the decisions themselves, especially when it comes to ration costs. Feed suppliers have benefits in selling more concentrates, while farmers should make the technical-economical best ration.

In modern dairy farming use of herd management systems is almost mandatory, because the amount of collected in-farm data nowadays goes beyond human capacity. Modern herd management systems collect data form different in-farm sensors and assists to farmer with the well thought out reports that helps to manage dairy herd.
The data management system serves as on-farm advisor for farmer and farms workers that suggests about the manipulations that needs to be done (service, removing from group, moving to nursery etc.) based on the all the data, collected from farm animals.
By inputting the information about important events of cows life (service, calving, etc.) it is possible to obtain a proper herd documentation that is suitable for quick redacting and covers all cows life events in quick and easy accessible way.
In local dairy farms that has more than 100 dairy cows, herd management system is not rare phenomenon. In different farms are used different management systems depending on the manufacturer of other in-farm sensors, used in holding.
By introducing herd management systems in farm, in addition to easier manageable herd documentation, there are observable significant decrease of length of calving interval and days open, due to better heat monitoring, as well as decreased somatic cell count in milk and number of health disorders in farm, due to better monitoring of monitorable traits (somatic cell count, number of steps per day, body temperature, etc.)

Ketosis is often caused by the fact that after calving a cow doesn’t consume enough energy to meet her needs. A cow can get very sick from ketosis, which causes her to lay down a lot and eat less which increases the effect of ketosis. A cow that has a BCS of >3.75 at calving has a greater risk at ketosis. A high BCS at calving occurs when an energetic ration is fed in the dry period. Dried off cows that eat a lot of energy before calving have a lower rumen fill, because they eat less dry matter. Which results in a lower intake capacity after calving. The BCS camera enables the farmer to monitor his cows closely in vulnerable periods and adjust the feed more specifically when the BCS of a cow is increasing too much. As discussed above a cow can be too fat at calving but it can also have a BCS of <3.25 which means there was too little energy provided in late lactation and dry period. This increases the risk at reproduction problems and a lower milk production during the lactation. Thereby high milk producers might drop below a BCS of 2.75 which can also cause problems regarding the reproduction. And lastly when a cow has a BCS > 3.75 at dry off this might cause problems at calving and reproduction in the next lactation. If the BCS is scored regularly using the BCS camera, a more specific feeding management can be applied on the farm. Group averages can be assessed and feed can be adjusted according to the BCS. Thereby, individual cows are monitored. While improving the feeding strategy to prevent ketosis the farmer might also see an improvement in reproduction, higher milk production and a better health of the herd. The camera can be placed at a selection gate after the milking parlour or robot and therefore is a stress-free method for determining BCS.

A bacteria which often causes problems amongst dairy cows is E.coli, a clinical form of mastitis. E.coli spreads fast and has severe consequences for the cows health. Symptoms occur when the infection is at its worst. An infected cow becomes sick, has a fever, loses appetite and the udder is swollen and feels hard. If the farmer does not treat the cow right away, the possibility exists that the cow dies. A solution for this problem could be the sensor of Connecterra, Ida. This sensor is monitoring the behaviour of the herd but also individual cows. In the first week the system tries to ‘get to know’ all the cows and sets a baseline for their behaviour. Which afterwards makes it easier to identify a difference in behaviour per individual cow. A alert is given by the system when for example the cow is eating less, standing more and laying down less. The farmers can now go and check whether the cow is sick. If not, he can tell Ida and it will remember this, to prevent errors in the future. Mostly the sensor detects changes in behaviour much faster than a farmer would and the farmer can start treating preventive when certain alerts are given. Early treatment can include administering pain killers, inflammation inhibitors and application of liquids such as mint salve. Early detection of mastitis makes sure that the cow does not get very sick. She will lose less milk and has a greater chance at full recovery. Recovery will go quicker and start earlier. An early recovery will save the farmer money and labour costs. Also there is a chance that the farmer does not have to use antibiotics if E.coli is detected in an early stage. Subsequently it saves time because a cow that had to be treated in the beginning of the lactation needs a lot of extra attention during the remaining time of the lactation.

Students of Van Hall Larenstein University of Applied Sciences (VHL) have the opportunity to develop knowledge regarding grassland utilizing a digital grass altimeter to improve their own grassland management. Annually VHL has 10 grass altimeters available for students. When students decide to join the FarmWalk seminar, they can use a grass altimeter for the whole year under the condition that they complete a FarmWalk weekly and analyze the grass growth. These data are collected on the website “Grip op Gras”. By collecting these data consequently the website will show you FeedWedge of your farm. The aim of this opportunity is to create awareness among the students about grass growth, grass yield and a better knowledge (practical) about grassland management.
As a result, students can predict grass growth and create more effective planning, which can significantly reduce grassland losses and increase the quality of the grass. Moreover will be a better utilization of roughage and eventually feed costs will decrease. Although this is applied to the education program, it is also interesting for farmers who want to gain greater insight into the yields of the pasture and, for example, farmers who face difficult pasture planning with a significant number cows per hectare of home ground. Grass is the cheapest feed type available, when the utilization is optimized by trough effective planning and good quality, this will result in lower labor intensity.

The quality of a good grass begins when the grass is sown. You must take into account the result you want to see back in your grain bar. When sowing, choose a grass seed that fits the soil characteristics and mowing strategy. If the pasture is to be grazed then it is useful to sow a mixture of grass seed that is suitable for grazing. At the beginning of the growing season, growth steps should be planned. These can be designed by calculating the grass's growth and can be undertaken by means of different sensors; for example, the grass altimeter and the Pasture Reader. An advantage of the pasture reader is that this sensor also measures the grass concentrate. When starting with harvesting, it is necessary to ensure the mower is set to the most appropriate position: should the grass be conditioned or not; should the grass be spread wide or in tight swaths? When the grasses are mowed, the dry matter content can be measured. When the grass is already relatively dry, do not ted it too intensively in order to prevent degradation of the quality. When you start harvesting, it is recommendable to use an silage agent, which ensures that no spontaneous heating occurs and the grass will be well preserved. Finally, in order to prevent disturbance of the conservation process, ensure that the silage storage is properly covered.

Rumen acidosis occurs when a ration exists of too much concentrates with fast digestible carbohydrates. When a cow consumes too much of these carbohydrates relative to slow digestible roughage the rumen will acidify. Certain micro-organisms die when the pH of the rumen is too low, which causes the fermentation of the feed to be less efficient. Less vitamins can be obtained from the feed, and more toxins are produced during the process. By using the pH bolus the risk of rumen acidosis can be reduced. The sensors in the front of the bolus are measuring the pH and temperature every ten minutes and is implemented in the rumen. And data is send to the computer of the farmer or mobile device where the farmer can see the temperature and pH of the rumen. If there are no outstanding results in the pH of the rumen it displays that the ration is stable and there is no risk of rumen acidosis. Boluses are often used to optimize the feed management, and when the ration appears to be stable, they can be removed again. The bolus can detect rumen acidosis early and the farmer can change the ration when necessary. Also the drinking behaviour and effect of heat stress on can be monitored using the temperature measurements of the bolus. Overall when the farmer will improve his feed management and this will also have a positive effect on fertility, the immune system and milk production.

At VMS farms the time in a waiting area or collecting pen is an ineffective state from a cow perspective. In a milking stall, the number of minutes for a milking can vary a lot between cows. One reason for this difference may be cow traffic and how long a cow has to wait in the collecting pen. The task of the collecting pen is to get a balanced flow of new cows for milking. The cows should move as straight as possible into the VMS, both on the way in and out. A maximum of 2.5 hours in the collecting pen / away from the stall area increases animal welfare, reduces the risk of production loss and lameness. It also saves working hours when you don´t have to move cows. Claw health also gets worse with a longer waiting time. The size of the waiting area must be such that it works as a reasonable buffer to handle swings in flow of cows given permission to be milked. The flow is, among other things, regulated by feed and the rate is controlled by the number of cows in a group in combination with the setting for milking permission relative to the number of VMS.

By monitoring the cows average time in the collecting pen with positioning, milking time registration (time away from the cow unit) for a group of cows or gate monitoring, one can investigate how the cow traffic works on a specific farm. You might have to adjust the size of the VMS group or adjust the number of cows getting permission to be milked. In addition you can get an overview how the flow works during the day and night, are there any daily variations? Is there any variations between cows and if so how can we help the cows that need help to get in and out from the collecting pen and into the VMS. By cow positioning you can see if there is something in the collecting pen that the cows avoid and that can be improved.

Within the herd there is always competition. Dominant cows will always take the fresh feed first. Which makes the newly introduced heifers more vulnerable for health issues due to lack of nutrients and energy in the feed. In addition more feed intake results in more milk production. A solution to this issue is to make sure that feed is always automatically pushed by a robot. When feed is always available, heifers will also have chance to eat fresh feed. Subsequently, to perform optimal a cow has to eat at least 10 to 14 times in 24 hours to keep the pH-level in the rumen stable. By pushing the feed frequently a farmer creates the ability for every cow to have these meals. Also when the feed is pushed less frequently this causes stress in the herd. Cows that have a lower rank in the herd will eat faster and smaller portions. Using Juno the farmer will save time. He doesn't have to interrupt other activities during the day to go and push feed. In addition, the feed is also pushed by night, therefore the cows are more active by night. They will eat more and even go more to the milking robot during the night. This results in less “waiting” cow for the milking robot during the day. It also prevent competition in the herd and cows' feed efficiency will improve. A better feed efficiency can gain you up to €250,- per cow per year. (See BPG Nutrition).

In addition to the roughage, the concentrate is sometimes also supplied to the feed fence. This gives the dairy farmer insufficient insight into the concentrate intake per cow. In addition, dominant cows will displace the young heifers at the feed fence. This has adverse consequences for both; dominant cows that consume more concentrate than their needs, there is a high risk of fattening and rumen acidification because the pH drops in the rumen. Heifers who take in too little concentrates don’t have enough energy and therefore develop a growth retardation. In addition, a lack of minerals gives more chance of a bad start-up after calving. In a concentrate box, cows can individually pick up their concentrate. These are equipped with cow recognition and can be in different places in the barn. Each cow carries an identification sensor around his neck and receives the right amount of concentrate. The amount of concentrate is determined on the basis of her milk production, age, BCS and lactation stage. The concentrate box provides insight into the concentrate intake and distributes the intake throughout the day, this helps to prevent rumen acidification. In addition, the concentrate feed can be adjusted automatically per animal and per period. If no feed intake takes place, this is also recorded. This can be an early signal for health problems. The concentrate box prevents competition, because each cow has access to its own portion of concentrated feed.

The use of data has been key to effective management of dairy cows for many years but in this time of “big data” and the increase in number of sensors used on farms the increase in amount of data is exponential.
The challenge is to ensure all this data is used to the benefit of the business, the animals and the labour and not simply collected and unused. The data produced by sensors and systems is generally represented in three ways;
• Indices – system gives an overall rating by combining different measures into an index.
• Percentage probability – giving chance/likelihood of an incident/condition occurring.
• Categorise cows – number of cows showing certain trait eg oestrous, mastitis, lameness etc

The challenge to us as dairy animal managers is to combine this data into a means by which it is used – an action list of cows to concentrate on that is often the most applicable but it must be readily understood and communicated to ourselves or our team members, either as hard copies or increasingly through hand held electronic devices – smartphones etc. This combining of the data must be done automatically and not manually as this is ineffective use of skilled labour.

When deciding what system or systems to install on the farm it is crucial that dairy managers critically assess the compatibility of the data streams. Ensure that the decision made suits the farm’s individual needs and that the huge amount of data available is used effectively and not ignored because of data overload or difficult to access daily.

Critical to the effective management of data is the level of false positive alerts resulting in wasted time, poor decision making and a permanent loss in the level of confidence in the system. Staff facing such inaccuracies will become sceptical of the system and adopt methods of working that do not fully utilise the benefits that data can bring to the management of the dairy cow. “Unpolluted” data is core to a successful business – particularly where farms rely on analysis of large quantities of data to make crucial decisions and ultimately survive.
The solution to high levels of false alerts or indeed too few alerts is to access the system routinely and link all alerts with specific farm based physical cow knowledge, using the lists produced to check specific animals. Adding cow specific behaviour into data enables the system to incorporate such animal behaviour into its alerts.
In addition to the introduction of cow specific behaviours into the data set, the alerts thresholds can be altered to ensure that alerts level is correct, not too many and not too few. A continual process of feedback is required to ensure that action lists produced are legitimate – data cannot and should not be used in isolation but worked with alongside and reacting with physical data/behaviour which is observed on the farm. This process can then lead to the formulation of farm specific operating procedures.

Critical to the effective management of data is the level of false positive alerts resulting in wasted time, poor decision making and a permanent loss in the level of confidence in the system. Staff facing such inaccuracies will become sceptical of the system and adopt methods of working that do not fully utilise the benefits that data can bring to the management of the dairy cow. “Unpolluted” data is core to a successful business – particularly where farms rely on analysis of large quantities of data to make crucial decisions and ultimately survive.
The solution to high levels of false alerts or indeed too few alerts is to access the system routinely and link all alerts with specific farm based physical cow knowledge, using the lists produced to check specific animals. Adding cow specific behaviour into data enables the system to incorporate such animal behaviour into its alerts.
In addition to the introduction of cow specific behaviours into the data set, the alerts thresholds can be altered to ensure that alerts level is correct, not too many and not too few. A continual process of feedback is required to ensure that action lists produced are legitimate – data cannot and should not be used in isolation but worked with alongside and reacting with physical data/behaviour which is observed on the farm. This process can then lead to the formulation of farm specific operating procedures.

When giving your cows access to pasture it is hard to determine how much dry matter they consume. It is important to know this because this is how you can determine how much silage you have to feed the cows to maintain milk production levels. Energy and protein in the feed must be in the right balance for the cow to be able to use both to produce milk and stay productive. Feeding in the stable needs to be adapted to the amount of fresh grass intake the cows have outside. A farmer can do a so called FarmWalks, which he has to do at least once a week in all paddocks he has, doing this he can use different devices to determine availability of dry matter in fresh grass. There is for example the feedwedge, which measures the height of the grass, and uses this to calculate the available amount of dry matter in the pasture. Next to the available amount of dry matter, the program calculates the demand of the herd in dry matter, based on the number of cows, the amount of concentrate the farmers is feeding, the required pregrazing level and the required post grazing residual. All this information is displayed in a graph. By displaying all this information it is easy for the farmer to see when there is a sufficient amount of grass, or when he has to feed silage to keep up milk production. When a lot of grass is available after moving the cows to another paddock the farmer can see this in his graph and choose to mow for example. Using the FeedWedge can make your grassland management more efficient and accurate.

Annemari Polikarpus and David Arney
As dairy herds get bigger across Europe the ability for farmers to give individual attention to their cows becomes increasingly unfeasible. Identification of health problems may go unnoticed until a late stage of the progress of the disease, when treatment is more costly, less effective and the damage to the animal’s productive potential has already been done. The order in which cows enter the milking parlour can be routinely collected in precision livestock farming. This entrance order is usually quite stable, but if cows are sick or injured they may enter the parlour in a different position to usual in the entry order. Maybe because they are fearful of pain in the parlour or during the milking process, or because of their sickness their position in the social hierarchy is affected. A study in Estonia looked at the effects of impaired on health on the change in the order that cows enter the milking parlour. This was found to be true for cows with mastitis and with metritis. The regular monitoring of milking order, and flagging of changes in this order, could be an effective and low-cost tool in the early identification of the presence of sub-clinical disease in individual cows in large loose-housed dairy farms. While such a system is not currently in place, Delaval and other parlour milking equipment providers do record routinely the ID of cows when they enter the parlour and farmers could use this data source to identify changes in the order and alert them to individual cow problems.

In modern day agriculture one of most excluded branches is organic dairy farming. In organic dairy farming the largest emphasis is on cow welfare. The common assumption is that in loose housing system with all year access to grazing and walking area is not suitable for the best option to ensure the closest to optimal conditions for cow welfare. Nowadays there are organic farms that brakes that assumption and leads by example that it is possible to grant optimal living conditions for cows, kept and fed according to organic farming rules.
The farm in focus was established in year 2004 with only 12 dairy cows and in year 2018 it has increased to 89 animals with average age 3.4 lactations (in year 2017 in herd was introduced 23 pregnant heifers). In year 2014, with the support of European Union, was built modern cowshed, according to organic farming rules, and in timespan from 2015 to 2018 in farm were introduced different modern technologies. At the end of year 2018 in farm were introduced herd management systems, neck collars with location tags, automatic milking system, semi-automatic climate control system, feed pusher robot and automatic fodder feeding stations.
Throughout the years in farm is observable tendency for milk productivity increase (in year 2018 it was recorded on 8560 kg per one cow) and steady somatic cell count in milk (around 220 – 250 thousand in 1 mL-1). With the introduction of feed pusher, cows tended to be calmer and with that improved feed intake and efficiency.
The heat monitoring and service efficiency rapidly improved after the introduction of herd management system and in year 2018 the average calving interval was 387 days and average number of services per one calving was 1.4.

Cows need protein to produce milk. Urea gives an indication of the balance between protein and fat in the ration and monitors the protein efficiency. The urea number in the milk is an indicator of the nitrogen utilization of the cows. When you combine the urea number with the protein content in milk you can see if your balance between protein and energy in the ration is all right. The unlimited feeding of protein does not result in an efficient nitrogen utilization because a cow needs products with carbohydrates to be able to utilize the nitrogen in feed. Thereby protein is very expensive, so a farmer can save costs by optimizing protein efficiency. The urea number indicates how much protein had not been used by the cow. So a high urea number means the urine contains a higher concentration of protein. It is therefore important to gain timely insight into this.The DeLaval HerdNavigitor contains an urea meter that can help to gain insight into protein utilization. By continuously measuring the urea in the milk with an urea meter, it can be assessed whether the ration is optimal and can be adjusted quickly if the urea number is insufficient.The advantage of an urea meter is that ration can be optimally adjusted, so that little protein in excreted in the urine. This saves a lot of money, and also farmers get paid for the amount of protein in milk. So if protein efficiency of the cow is higher and the protein content in milk goes up, the famers revenues will increase.

Negative energy balance and disturbances in the metabolic status is a common problem in fresh cows. Many times, problems like ketosis doesn't come alone. One problem can lead to another, as a domino effect, especially in the critical time around calving. Over-conditioned cows have a higher risk of developing ketosis which in turn leads to a higher risk of left displaced abomasum (LDA). Metabolic problems in the fresh period has also a connection to reduced reproductive performance later on and a higher risk on culling. Many dairy farms also have undetected issues with sub-clinical ketosis where the metabolic process is disturbed and the performance of the cow is suppressed but no clinical signs are seen. Continuous monitoring of the keton body β-hydroxybutyrate (BHB) by DeLaval Herd NavigatorTM will detect both subclinical and clinical cases of ketosis and allows for fast treatment and recovery and improve the overall milk production and health in the herd. Managing clinical as well as subclinical ketosis in time will not only increase the milk production and reduce the risk of early culling but also lower the risk of other diseases and domino effect consequences of the metabolic disturbance. Monitoring the BHB level gives both peace of mind, healthier cows and more milk in the tank.

Monitoring fresh cows is a real challenge for dairy men in a free stall barn. Cows are free to eat, rest and walk around as they please. And you as a manager are supposed to register that the individual cow is in good balance.
The fresh cow is new in the social environment and in the same time she is in at critical period of her life. Statistically she has an increased risk for metabolic disorder as well as health issues such as mastitis and metritis. In any case of disturbance it is of great importance that the disorder is detected early and that the cow is properly taken care of. Sick cows tend to be less active and they tend to lay down and rest more often. This change in activity can be detected with most activity meters. In early lactation it might be some difficulties because the time has been too short for equipment to calibrate. Another early signal for any kind of health disorder is reduced appetite. This can be difficult to discover early in a free stall barn with total mixed rations. Some barns have feeding stations for concentrate. Left-overs of concentrate is a good signal of some kind of disorder. Another way to monitor cow health during the first "high-risk-weeks" of lactation is to follow the milk lactation curve. The milk yield is expected to increase, and in cases it doesn't it can be a signal of some kind of disorder.
An early and correct basis for decision is favored if there are many sources of information. To combine information about activity, appetite and milk lactation curve during the first 30 days in lactation gives the dairyman a better tool to monitor his fresh cows.

In the fast pace of life and events, it is important to find out all information about the animal and its production as soon as possible. Many of available dairy sensors give farmer information about the condition of dairy animal, but there still are information that could be crucial in determination of the health, wellbeing and feeding condition of dairy animals. The small milk laboratories in automatic and parlor milking systems are used to obtain data about milk composition and quality (milk fat and protein content, lactose and milk urea content as well as somatic cell count in milk).
From obtained data it is possible to determine cows metabolic state (milk fat and protein ratio), feed efficiency (milk urea content, milk fat content), udder health (somatic cell count) etc. It also allows to separate the milk with poor quality from sellable milk (the electroconductivity sensors in milking systems).
By introducing the small milk sample laboratories in the milking system, it became possible to faster evaluate and improve feed ration, treat udder inflammation, monitor cows productivity etc.
By introducing small milk sample laboratories in farm, the most significant impact was on the metabolic disorder count (decreased by 25%) and udder inflammation monitoring. In average one case of mastitis were spotted 1.8 days faster than appeared first clinical signs.

Antibiotic reduction is a major point of attention throughout Europe and this forces farmers to work in a preventive matter. Sensor technology can help farmers to detect problems earlier and thus treat them earlier. There are a lot of sensors that detect health problems. Connecterra’s sensor the Intelligent Dairy Farmer’s Assistant (Ida) is one of these sensors. Ida registers eating, ruminating, lying, walking, drinking and standing behaviour and it recognizes when the cow is in heat. Compared to other sensor technology Ida is a self-learning system, based on machine learning and feedback from the dairy farmer’s information. The farmer gets messages in the app of Ida about deviating behaviour and the farmer can immediately take action. Ida detects cases of mastitis and metabolic diseases about 24-48 hours before they become visible to the farmer. The benefits of this earlier detection is that early treatment can prevent that the cow becomes seriously ill, the milk production decreases and a lot less antibiotic has to be used. Which will lead to increased technical results and a longer life span and life production. The longer a farmers works with the system, the better it will know the farm and be able to predict what’s going on with a cow and thereby give an advice about how to act.

In dairy farms with loose housing system with limited human contact it is quite hard to notice every cow in heat and be present at every calving. Therefore, in some dairy farms, more often are used rumen boluses that read data about cow temperature, activity and rumen pH. Data from boluses are collected in computer program that makes analysis and gives best predictions of different cows’ life events.
In family owned farm, in the beginning of year 2018 were introduced 42 rumen boluses. The information about cow daily activity serves as indicator for heat detection, data about body temperature are used to prognose calving and rumen pH results are used to evaluate the quality of feed ration, cows metabolic state and quality of rumination.
The introduction of boluses lowered number of days open (from 148 to 123 days) as well as decreased number of services per conception (from 2.3 to 2.1) mainly due to data, now available for farmer.
The system in farm also gives additional information about cow’s body temperature that can serve as indicator for different inflammatory or metabolic processes in rumen or overall cows body. In past, from farmers perspective, data from boluses showed significant effect on the precision of heat detection and prognosis of the most suitable time for service as well as on the management of cow health condition in farm.

Rumination is important for cows, when the re-chewed feed is swallowed together with saliva for the second time. On average, a healthy cow ruminates 8 to 10 hours a day. The importance of ruminating is to reduce the particle size and increase the surface of the food. This helps the fermentation process, to maintain rumen pH, reduce acidity and makes absorption of nutrients from the food easier. The ruminating activity says a lot about the health of a cow. A cow that gets ill will eat less than usual. As a result, the cow will ruminate less. It is very hard for a farmer to record this kind of behaviour, he can go and count the number of times a cow is chewing before she swallows to see if her rumination activity is sufficient. However this is very time consuming to do for every cow. Sensors that record rumination time can help a farmer. Rumination sensors offer the solution for the early detection of health problems. The sensor continually measures the rumination time of each individual cow and an average is formed. When the cow deviates from her average rumination pattern or deviates from the flock, the farmers receives an attention. Early detection of health problems ensures that the cows are treated immediately before they become seriously ill. This prevents high veterinary costs and saves time, antibiotic, milk loss and therefore money. Sensors detect 24/7.

Many dairy farmers feed the cows by using a mixer feeder. In most cases it has to be loaded with the different feed types and this requires a lot of time. As a result, cows are supplied with fresh feed every 1 or 2 days. The feed must be regularly pushed in by hand or some farmers push this by using the tractor. All this does not contribute to sustainable, efficient and optimal farm management. The Lely Vector is an automatic feeding system that provides the cows with fresh with the least possible labour effort. It takes the dairy farmer once every three days to fill up the feed kitchen, do an inspection and conduct periodic cleaning. This work can be planned in advance. Filling the mixing and feeding robot with the feed gripper offers the opportunity to mix many different types of feed. With every bite of a feed type, the system weighs the feed and corrects the feed grab automatically to the exact amount that the cows need. That is why the cows are always fed the exact same amounts of feed. The Vector can improve feed management and saves on average 8 hours per week. On an annual basis, this is a saving of 416 hours per year. It is a very flexible system and you determine your own feeding regime. Each feed strategy can be applied. It can be divided into different rations over different groups of cows. The Vector knows exactly where and when fresh feed is needed and the supplies it.

The heat detection, done without any technologies could be challenging because of small number of workers and high number of animals in dairy farms. The technology that is most commonly used for heat detection in dairy farms is step counters of pedometers, assigned individually to every animal.
The pedometers are showing not only increased activity that usually means that cow is in heat, but also decreased activity that usually leads to conclusions that animal has leg or claw problems or health disorders. Use of step counters positively impacts the length of calving interval and number of calves obtained from one cow, not only per year, but also per whole cows life.
The introduction of pedometers in dairy holdings usually leads to decreased number of missed heats, properly assigned service time and early detection of lameness cases. In different local studies by taking local farm animals, it was determined that use of pedometers also showed positive impact on dairy cow longevity.
In the may Latvian dairy farms step counters are introduced as addition to automatic milking systems and herd management systems to collect data about animal activity and location in cowshed.
In farm, where step counters were introduced in year 2010 the number of missed heats lowered by 20% and number of services per conception were reduced by 0.4 times. Average calving interval was shortened by 64 days. The number of early detections of lameness cases increased by 35%.

Nearly every dairy barn is equipped with electrical components and automated tools (e.g. in the milking parlour, concentrate feeders, manure scrapers, selection gates…). When the electrical system is not properly grounded or its insulating material is affected, unwanted stray voltage may occur in the barn. Unfortunately, the accurate diagnosis of stray voltage issues is still a bottleneck in practice: it can be a long, strenuous process for dairy farmers.
Cows are very sensitive to stray voltage. Possible symptoms include nervous behavior during milking, such as refusing to enter the parlour, kicking off the milking clusters and defecating more frequently. Their drinking and feeding behavior can also be affected, depending on the source of the issue. Cows will not be milked out properly, increasing the risk of elevated cell counts and mastitis.
Preventing stray voltage starts at the beginning, during the designing and building phase of the barn and milking parlour. All metal parts should be insulated and grounded, including the wire mesh in concrete walls. The electrical enclosure and equipment ought to be also installed properly. In case one suspects stray voltage might be at play, the help of a professional should be invoked to find the source of the problem.

The transition period is normally described as three weeks before until three weeks after calving and is a very critical time for dairy cows. Keeping cows healthy and in adequate energy balance in the transition period is vital for a successful and profitable lactation. Early detection of diseases and feeding issues are key in this time period. Transition cows need to be kept under close surveillance and at the same time it can be difficult to keep them in a separate physical group for special monitoring and care. Unnessessary group changes should be avoided if possible as that can create stress in the herd. Instead virtual groups can be created that places these cows in a "VIP" status. Depending on management system, the virtual groups can be created in different ways, either as a special function or by using a filter in your normal groups. The VIP virtual groups can be more closely monitored and followed up on data like milk production, activity changes, feed intake and other available sensor data on the farm. Special attention reports can be created for your VIP cows so that those cows are the first you take care of in the morning. The management of the transition cows will set the direction of the rest of the herd and the performance during the whole lactation for the individual cow. The fresh VIP cows in an automatic milking system can be given special milk permission settings to make sure that they are milked at least three times per day.

Often technology is proposed as a way to help farmers in order to get more productive. However, often it is not the desire to increase milk yield per cow that motivates farmers to consider a new set of technology such as e.g. a milking robot, yet the need to organize labor more appropriately. When a farmer exceeds a number of livestock (say more than 200) he will be in need for an additional working force. When a farmer is not able to find an adequate candidate with a passion for the field and a long term engagement, this might convince him to consider a robot. Is this, however the right reason? This illustrates how PLF technology also needs to be considered in relation to the larger societal system in which farming takes places: maybe we need to invest in a match-making system between skilled labor and dairy farmers? If a robot makes it possible that the ageing farmer keeps on helping his relatives that have taken his farm, does this automatically mean that this is to be considered as something normal.
What is needed to tackle this problem is a serious research and debate about the relationship between technology and labor efficiency. It needs to be identified how the labor system in a particular regions can be optimized and how the role of technology and sensors can be instrumental to a farming labor experience that is based on the joy of farming life, and not on a coping strategy to keep on maximizing productivity.
Project-action on both European and national levels is much needed.

Feed is important and contributes to animal health and high milk production. Fat cows (BSC 4 or 4>) are a risk during start-up after calving. When a cow is too fat it causes an increase in level of leptin in the blood. Leptin decreases the appetite of the cow, which leads to a lower feed intake around calving. The key factor is to feed the cow enough dry matter before calving, because this influences the feed intake after calving. But to keep the cows from getting fat by feeding a low energy ration. A cow with a high negative energy balance has a higher risk at ketosis and fertility problems. An optimal feeding strategy for the dry period is therefore essential.The BCS camera makes scoring a lot easier and takes away the inaccuracies of manual assessment. The BCS camera is placed in the milking parlour or on a selection fence. Every time the cows go under the camera, a 3D image is taken from the lower back. As soon as a cow deviates from previous scores, an attention is automatically sent to the farmer. In such a way the farmer can keep track of his cows, to see if they will not get to fat. The use of the BCS camera contributes to an optimal feeding strategy and enables maximum feed efficiency. Warnings if a cow, group or livestock is over- or underfed allow the farmer to adjust the ration in time or to move a cow to another feed group. The scores can easily be shared with veterinarian and feed supplier.

Small herds have specific problems with heat detection. Numerous factors affect the expression of heat including, housing arrangement, floor surface, feet and leg problems and status of herd mates. The number of mounts a cow receives increases with the number of cows that are in heat simultaneously up to about 3–4 cows in heat. Cows that are themselves in heat, coming into heat or were recently in heat are most likely to mount a cow that is in heat. Cows that are pregnant show less interest in mounting other cows that are in heat. In smaller herds, with lower numbers of open cows, the likelihood of more than one cow being in heat on any given day becomes less, consequently, making heat detection more difficult. In addition to this lack of mounting mates, small herds face specific problems which can lead to extended calving intervals, including labour availability, possible housing deficiencies and shorter oestrous caused by higher yields. The 4D4F website details the different technologies available to cow managers. Sensors can monitor cows 24/7 and produce daily action lists for cow managers informing them of cow identity and optimum time for insemination. With a benefit of 4 euros per day from reducing calving interval - a 100 cow herd reducing calving interval from 420 to 400 days with the use of sensors monitoring 24/7 will see an 8,000 euro increase in profits and will in addition benefit from lower veterinary treatments costs and lower labour requirements.

Small herds have specific problems with heat detection. Numerous factors affect the expression of heat including, housing arrangement, floor surface, feet and leg problems and status of herd mates. The number of mounts a cow receives increases with the number of cows that are in heat simultaneously up to about 3–4 cows in heat. Cows that are themselves in heat, coming into heat or were recently in heat are most likely to mount a cow that is in heat. Cows that are pregnant show less interest in mounting other cows that are in heat. In smaller herds, with lower numbers of open cows, the likelihood of more than one cow being in heat on any given day becomes less, consequently, making heat detection more difficult. In addition to this lack of mounting mates, small herds face specific problems which can lead to extended calving intervals, including labour availability, possible housing deficiencies and shorter oestrous caused by higher yields. The 4D4F website details the different technologies available to cow managers. Sensors can monitor cows 24/7 and produce daily action lists for cow managers informing them of cow identity and optimum time for insemination. With a benefit of 4 euros per day from reducing calving interval - a 100 cow herd reducing calving interval from 420 to 400 days with the use of sensors monitoring 24/7 will see an 8,000 euro increase in profits and will in addition benefit from lower veterinary treatments costs and lower labour requirements.

Having healthy and productive replacement stock is vital for the future successes of any dairy herd. Therefore, calf management is a very important process for both short- and long-term benefits. Managing any health and disease risk is a vital part of this; to help benefit in terms of fertility, health and production in the future. Fever tags are a temperature monitoring ear tag that measures the core temperature of the calf from a probe in the ear canal every 15 minutes. Once the threshold of temperature is breached over a certain time period, this then signals an alert and the ear tag will flash. This allows any farmer or stock person to have an early indication of disease or health problems up to 72 hours before any visual signs can be seen. As a result of this, any at risk calves can be treated before any further health issues occur, such as reduced appetite or dehydration. As well as improve health and management of the calves, farmers can monitor the spread of a disease and also make better use of preventative treatments and anti-inflammatory medication, thus reducing antibiotic use.

The amount of farms with employees worldwide is growing steadily. On the one hand this is a positive evolution of the dairy farming industry, but this means farmers need to become managers. How can these farm managers be sure all employees perform their work according to the vision of the farm manager?
Writing Standard Operating Procedures (SOPs) for a specific farm has a strong added value. By starting to collate all the activities step-by-step and discuss procedures, more insight into “usual” activities will be created. Standard activities which are normally performed automatic will now be undertaken more consciously. Besides it will be much easier to instruct employees or farm visitors. When SOPs are well integrated into the farm management system it is required for employees to follow up these procedures. When employees are familiar with their tasks the hazard of making mistakes will decrease, and workers can be substituted due when, for example, in the case of sickness. The major advantage for working with SOPs on dairy farms is that routine work will provide a better overview of work and, therefore, better planning. In addition less indirect hours will be incurred, making it more effective. Moreover the SOPs can make more use of the quality of the work. A clear SOP can, therefore, provide greater satisfaction in the long term.

Some farmers like to use grazing in order to be committed to legal standards, whereas other farmers just like the view of grazing cows. Why should grazing at farms be applied? What are good examples? Years ago, it was customary to applied grazing at every farm. The intake of a sufficient amount of grass was a prerequisite for milk production. Moreover, grass was the cheapest feed type available and still is. On the other hand, we did not yet have these current ambitious production targets of feed the whole world. Additional feed is essential now to meet the necessary peak production. However in the case of this abstract the focus will be primarily on grasses. Why should grazing be applied, what are the benefits? Firstly by grazing, the cows are naturally manuring the pasture themselves. Secondly, cows are mowing the grasses themselves, making space for new grasses to grow. Moreover cows feed themselves. In addition to being labour saving, grazing delivers added value to the soil life as well, which is essential for grass quality. Of course cows cannot place fences themselves, but nowadays modern labour saving technologies like the Lely Voyager are available for jobs like this.

This year’s summer has led to a dramatic shortage of pasture and forages. Therefore, farmers have to look for alternative feeds. A solution could be to let the cows out in the deciduous forest to graze leaf and lily. Farmers need to keep a track of the animals - daily supervision is a requirement in Sweden. At a big dairy farm in Sweden, Wapnö http://www.wapno.se/ some 100 ha of forest has been fenced and around 200 heifers has been let out in the forest to graze.
To be able to track the heifers, some of them have been provided with GPS-units. They use the same robust equipment’s and technology that is used for keeping track of reindeers in the north of Sweden, Pellego, see https://www.followit.se/livestock/reindeer.html.en. It is important that the units have long duration time (long battery time), that several positions are determined per day, about once an hour, to avoid the risk of missing positions due to signal shadowing of satellite signals from the tree coverage. Of course there must be good contact to antennas, like the GSM-net or local antennas in the area.
The following recommendations should be considered: The transponder should be placed on the animal´s neck to obtain a good chance of receiving the satellite signals as well as programming the GPS unit to determine several signals a day to avoid missing positions. The battery capacity and the frequency regarding the positions are crucial factors for the robustness of the equipment: the more positions that are determined per day, the longer battery life is required. New innovations regarding power, battery life, and adding on sensors that supervise the status of the animal (health, fertility) are entering the market which can make this technology more useful in various situations and needs

A challenge in running a dairy farm is noticing when a cow is having health issues. Since farms are scaling up a farmer has less sight on the individual cows. By introducing sensors in the daily management routine a farmer can keep track of the health of the cow by tracking her progress in the management system. The Herd Navigator is a sensor which takes samples from the milk, and analyses these to check whether a cow is showing any signs of for example ketosis, mastitis, heat and whether she has fertility problems or her feed efficiency is sufficient. By combining this data with regular management data available to the farmer for example the milk production data, protein and fat contents in milk, in between calving time and cell counts the farmer is able to get an overview of performance and health of the milk producing dairy cows. The Herd Navigator keeps track of several aspects concerning the animal welfare of the cow, one of them is energy balance. By measuring the Beta-hydroxybutyrate concentration in milk the Herd Navigator can determine whether a cow is developing subclinical ketosis. A farmer can implement adjustments for example make sure that feed is accessible at all times for the cow and prevent stressful situations.

Heat stress has long been recognised as a problem in Mediterranean countries, but global warming has increased its importance in all European dairy farms.. The number of days with temperatures over 30 C in southern UK has doubled in last 20 years. Heat stress and subclinical effects can result in reduced output and suboptimal herd fertility, and can be seen with ambient temperatures as low as 20 C. Increased natural or forced ventilation can be used to mitigate the challenge of hot summers but misters and even refrigeration may be necessary. Rumination sensors can be used to test the efficacy of this action on individual cows, and even highlight a problem in the first place. The management of this ventilation however must be considered and decisions required for its effective management should not be made from subjective human criteria but from accurate data derived from embedded sensors throughout the barn which integrate the data with humidity data – and produce a Temperature Humidity Index. Such systems then activate fans and or inlet manifolds so the temperature is kept close to optimum for health and milk production. Such systems can be retro fitted to existing buildings or incorporated in new cow barns .As temperatures are forecast to rise, the modern cow manager will have the ability and technology to incorporate accurate sensors in the cow barns to ensure cows will not suffer heat stress and have health and production compromised.

Heat stress has long been recognised as a problem in Mediterranean countries, but global warming has increased its importance in all European dairy farms.. The number of days with temperatures over 30 C in southern UK has doubled in last 20 years. Heat stress and subclinical effects can result in reduced output and suboptimal herd fertility, and can be seen with ambient temperatures as low as 20 C. Increased natural or forced ventilation can be used to mitigate the challenge of hot summers but misters and even refrigeration may be necessary. Rumination sensors can be used to test the efficacy of this action on individual cows, and even highlight a problem in the first place. The management of this ventilation however must be considered and decisions required for its effective management should not be made from subjective human criteria but from accurate data derived from embedded sensors throughout the barn which integrate the data with humidity data – and produce a Temperature Humidity Index. Such systems then activate fans and or inlet manifolds so the temperature is kept close to optimum for health and milk production. Such systems can be retro fitted to existing buildings or incorporated in new cow barns .As temperatures are forecast to rise, the modern cow manager will have the ability and technology to incorporate accurate sensors in the cow barns to ensure cows will not suffer heat stress and have health and production compromised.

In the past, a herdsman’s notebook sufficed but with data coming from several sources - the parlour, feeding system, third party recorders, veterinary surgeons etc it is no longer adequate – and will lead to possible mistakes. In addition, with several data streams a certain amount of reconciliation will be required to bring all this data together in an accessible form and this is better done automatically on the internet.
Office based desk top computers and even laptop computers are useful on farms but in the cow barn itself best practice would be single entry via an Android or IOS smartphone or similar tablets. Phone network coverage is not essential in that a farm based WIFI system would allow access to the web and “cloud” on which all data will be stored, manipulated and accessed. The WIFI system should be set up to avoid black spots with low conductivity to prevent frustration and allow herdsmen to check data whilst going about their normal work or at location of specific cows. Such a system is available to all farms with access to the internet.
Inspecting a cow directly making breeding judgements, daily management decisions etc whilst accessing full data held on the specific cow allows more accurate and informed decisions.
Single entry systems are likely to be more accurate and reduce the amount of work required – freeing up the herdsman for greater input in critical issues of cow care and stockmanship. The choice of actual phone is personal preference but ensure sufficient processing capacity and memory are available to avoid delay and frustration.

The use of data has been key to effective management of dairy cows for many years but in this time of “big data” and the increase in number of sensors used on farms the increase in amount of data is exponential. The fact that much of the data comes from different source and streams exacerbates the challenges.
The manipulation into an accessible form is both time consuming and complex, and therefore not good use of cow managers time. Use of cloud based system and effective use of the internet based systems is the most appropriate method of manipulation of this data.
This method is the only way in which artificial intelligence and machine learning of individual cow’s behaviour can be accessed which will result in more accurate of alerts and reduce the number of false positives - a challenge at present.
The form in which the final data is presented can be determined in part by the manager’s preferences, but generally comparison with historic data, benchmarking against known KPIs is an appropriate methodology.Cloud based systems will allow real time data to be collected and be shown to advisors with confidence. They will also result in more accuracy and a reduction in work – allowing this to be used in more business-critical areas or simply less hours worked and an economic saving and increased satisfaction.

The use of sensors in dairy farming industry can be seen as a quite recent phenomenon. More and more farmers are now beyond the first generation of activity meters geared at fertility management, moving towards more complex systems that also monitor data relevant for feed strategies and animal welfare. Since a lot of farmers are only just starting to work with these systems, the usability of the data for long term dairy farm decisions is still not at a mature point. In a few years, farmers will however have access to long-term data series, potentially supporting them in more long-term strategic decisions.

Sensor data is used to look at year-by-year results about animal welfare and feed management, but also on time investment on specific hours spent on specific tasks. For instance, what time has been spend on animal welfare management when comparing young stock breeding with the dairy herd. What has been the occurrence of diseases and how much time has been spent on treatment and with which success. Feedback of this kind can be drawn from sensor software and can guide dairy farms in case a strategic decision needs to be taken: for instance, will I keep on doing young stock breeding myself or will I outsource this activity?

Also in relation to feed strategies longer term data series could provide valuable information. What have been crucial changes over the years in terms of feed choices and what has been the impact on both milk yield and profitability. Sensor data can thus provide a kind of accurate feedback on the history of day-to-day decisions adding a new layer to strategic decision making.

It is very hard and would be time consuming to monitor the standing and lying time as well as the activity of individual cows. This information however can be strongly linked to the health status of each cow individually.
Through using activity sensors, the average lying time for your herd can be established. The concept of daily time budgets can be used to monitor this and allied with activity sensors located on the cows; either foot mounted or neck mounted, an accurate pattern can be established.
Leg mounted sensors however are the only ones that can gather accurate lying time data. It is commonly suggested that cows make more milk when they are lying down as blood flow through the external pudic artery increases by 24-28% when lying compared with standing up. Failure to achieve the required level of rest results in a significant stress response, causing increased lameness risk and vulnerability to health problems.
There are strong links to suggest threshold, and that all cows regardless of yield require a minimum rest period. Once this threshold has been reached a linear relationship may exist with trials showing that after 10 hours rest, every additional hour can generate 1.6 Kg of extra milk without an increase in DMI – simply owing to increased efficiency of milk production.
In addition to an increase in daily yield from appropriate length rest periods, the effect on cow health, a reduction in lameness, reduced cow replacement rates can be a significant economic and welfare driver.

The S.C. ERAGO NUCET SRL farm was completed in 2015 on a total area of 56,553 sqm using European funds and its own sources. The farm owns stables for the maintenance of dairy cows, youngsters and calves, a milk processing unit, local water supply system, local sewerage and manure management system, silos platform, sanitary filter, car disinfector, administrative facilities. Farm equipment is modern and complies with EU animal welfare and biosecurity standards.
Regarding the structure of the herd, the farm owns 506 animals in total, out of which: 233 lactating cows, 25 cows at rest, 53 heifers, youth 0-6 months 48 heads, youth 6-12 months 83 heads, youth 12-24 months 64 heads. The average daily milk production is about 7500 liters per farm, with 3.63% fat and 3.9% protein.
A major problem faced by farm managers was related to the correct and timely detection of cows in the heat, feeding according to production, health status surveillance, milking with records of each cow's production etc.
The solution was to purchase a farm management system, namely the GEA Herd Management Software Dairy Plan.
The benefits of using such a system are major, bringing a significant boost to the biological and economic efficiency of farm activity.

Lameness is one of the biggest and most widespread problems experienced by dairy farms. In any degree of severity, having a high lameness percentage in your herd can be very costly. The costs themselves can affect indirectly in terms of production, antibiotic use and labour; and also directly impacting cow health and welfare. Identifying lame cows by eye is still a popular method currently, however in response to increasing average herd size it will become important to be more efficient in achieving earlier lameness detection. The CowAlert system allows automatic lameness detection with the use of a pedometer containing an accelerometer. This measures activity levels, step count and standing and lying time; every day, 24hrs a day. This allows earlier and more accurate lameness detection, picking up problems that may not have been picked up by the human eye. With the use of CowAlert, farmers can better manage lameness problems sooner, allowing closer monitoring or in some cases antibiotic treatment. Overall the benefits are reduced antibiotic use through earlier detection, better herd health and welfare, reduced labour costs as well greater milk production potential.

Goats are seasonal breeders; their breeding cycle is heavily influenced by daylight intensity and length. To maintain as level a milk profile as possible in the “off season” - this tendency must be managed effectively. Naturally goats in Europe will start their oestrus cycles as the day length diminishes in the autumn. In order to get more pregnancies in the 'off' season, we need to influence the natural oestrus cycle of the doe so that she can breed when required by milk profile demands.
The use of remote light sensors and automated lighting systems as described on the 4D4F website are ideal for the management of lighting; optimising breeding opportunities and reducing labour requirements.
The management regime must manipulate the length of time the goats are exposed to light so as to simulate the daylight lengths experienced in the late summer - early autumn period. This requires sufficient light for a minimum of 16 hours per day for a minimum of 45 days, and it is recommended that the light intensity be 200 lux when measured at eye level of the doe. This can be easily verified by installing a free app on your smartphone. The length of light period is then gradually decreased by 1-2 hours per week, until 8-10 hours of light per day is achieved. It is very important that the breeding bucks are exposed to the same light regime so they are equally prepared for the breeding period. Approximately 6-8 weeks after the termination of the light treatment the breeding bucks should be introduced to the does, with fertile oestrus occurring 10-20 days after this.
Milk contracts do stipulate milk profile requirements, and this is a cost effective, non-invasive method of ensuring such commercially important criteria are met.

What is the real amount of dry-matter-content of the harvested grass, is one of the most asked questions of farmers during harvesting which stays most of the time unanswered. The dry-matter-content is besides protein and feed-value on of the most used characteristics of grass during harvesting in summer and making up the right ration for the herd in the winter. So, even it is important information for a farmer to know, it is still difficult and time-consuming for farmers to get this information by themselves.
There are several sensor-based yield measurements available which can be installed on the silage machines. For example the Pasture Reader. The Pasture Reader measures with ultrasonic technology the height and the density of the grass, this measurement results in the dry-matter-content in kg/ha. The Pasture Reader can be installed on a mower and/or quad. Besides ultrasonic technology also Near-Infra-Red-Spectroscopy (NIRS) is a possibility. NIRS can measure the dry-matter-content of grassland site-specific. NIRS is used on silage machines and therefore used for harvesting processes. With a deviation of 2% the NIRS-system is very accurate on measuring grass yield. The results are send wireless to a server, and software puts all the different data together in just one yield-overview. The NIRS-system can be installed on a loader wagon.

The benefit of utilization of a sensor-based yield measurement can provide farmers real-time information about their grass quality. Therefore making more accurate decisions to improve both yield and quality of silage to increase production of the dairy herd.

It is difficult to have a clear overview of the grass growth of all the pastures nowadays. The pastures became larger and the weather more instable, so to predict the grass growth and the dry matter content has become more complicated as well as creating an effective planning.
Using the platemeter, as described on the 4D4F website, and performing a FarmWalk weekly gives farmers the opportunity to create awareness about grass growth and grass yield. During a FarmWalk, farmers will walk through the pastures in a V or W-shape with the grass platemeter. The platemater records in 30 measurements the average amount of dry matter per hectare. As a result of performing a FarmWalk regularly farmers can predict grass growth better and create an more effective planning, which can significantly reduce grassland losses and increase the quality of the grass. Using the platemeter is not only interesting for farmers who only mow the grass as a way of harvesting but also for grazing, the use of the platemater is a useful tool. Maybe the added value will even be greater. Especially for farmers who face difficult pasture planning with a significant number of cows per hectare of home ground. Even in this last case the grass intake of the herd can be measured.
The platemeter will help farmers to optimize the utilization of grassland and will be useful by creating an effective planning and insight in the quality of grass. Therewith the cheapest feed type available will not only be cheap but also of higher quality for the cows.

Farms are becoming more efficient at identifying lame animals. There are however still costs associated with finding the specific causes. These costs can be through misinterpretation, leading to wasting administered antibiotics, as well as labour and time cost. How thermal imaging can be used is through measuring infrared radiation. Infrared radiation is directly affected by temperature, as with a higher temperature more radiation is emitted. With using thermal imaging cameras, specific causes of lameness can be found from areas of higher temperature. With this equipment, better diagnosis can be made for cause of lameness. For example, identifying which specific claw and area of the foot is the cause, or whether the problem is in the foot or a different area of the animal. The benefits from this include early detection and confidence when choosing course of treatment; resulting in less antibiotics being used and better welfare for the animals affected. Through early detection, there will be less severe cases of lameness, contributing to improved overall health of the dairy herd.

The success of automatic milking systems largely depends on the cow’s own motivation to visit the milking unit several times a day. The number of cows that need to be fetched twice a day should not exceed 5% of the herd. Ideally, the average milking frequency does not drop below 2.4 times per day. But what if it does?
The first thing to do, is to analyse the potential problem. By only looking at herd averages, you run the risk of glossing over potential problems in a specific subset of cows. Low-yielding cows at the end of their lactation do not need to visit the milking robot as often. The high-producing cows in their early lactation, on the other hand, should find their way to the milking unit easily, and reach a milking frequency of 3 times a day – or more.
Ultimately, the cow’s main motive to visit the milking robot is feed. If the number of visits starts to decline, check the concentrate dispenser in the milking robot. Also, palatability is key in “luring” the cows to the milking robot. Even minor changes in the quality or composition of the concentrates or forage at the feed bunk can alter the visiting behaviour of the cows.
But every farm is different, of course. General management factors such as herd size, access to pasture, barn design, type of cow traffic, … all have a huge effect on the overall milking frequency. Sick or lame cows will also be less motivated to go to the milking robot. Make sure your cows are in good health when you notice the visiting frequency starts to decline.

Farms are getting bigger, more automated and employees have to be hired to get all the work done. In a farm where multiple people are working, everyone conducts tasks works on one’s own way while they often have the same goals in mind. Even small family farms are sometimes struggling with discussions about farm management. So what would happen if someone suddenly took your job over? In the future tasks and processes are more supported and driven by data, the sensors that are used for monitoring, advice systems and machines to perform actions. The 4D4F website details a series of SOPs which can be tailored to the specific need of individual farms when adopting sensor and data analysis technology in dairy farming. By using these SOPs to set out protocols for specific processes or tasks within the farm, a farmer can make sure that other people will perform the task in the same way as he does. The benefits of protocols are evident: staff functions better on a large farm and work is easier to transfer to third parties on a smaller farm. Subsequently it saves time because meetings do not have to occur as often as usual. The farm management is going to run more smoothly and efficient this will save costs caused by errors from family members or employees. Also the technical results can be improved by working with SOPs because there is more clarity, constant execution of the work, correct information transfer and avoiding/ finding errors.